Click here to close now.


@CloudExpo Authors: Jennifer Gill, Dana Gardner, Elizabeth White, John Basso, Pat Romanski

Related Topics: @CloudExpo, Java IoT, Microservices Expo, Containers Expo Blog, Government Cloud

@CloudExpo: Blog Feed Post

MaaS – The Solution to Design, Map, Integrate and Publish Open Data

Data models can be shared, off-line tested and verified to define data designing requirements, data topology, performance, place

Open Data is data that can be freely used, reused and redistributed by anyone – subject only, at the most, to the requirement for attributes and sharealikes (Open Software Service Definition – OSSD). As a consequence, Open Data should create value and might have a positive impact in many different areas such as government (tax money expenditure), health (medical research, hospital acceptance by pathology), quality of life (air breathed in our city, pollution) or might influence public decisions like investments, public economy and expenditure. We are talking about services, so open data are services needed to connect the community with the public bodies. However, the required open data should be part of a design and then integrated, mapped, updated and published in a form, which is easy to use. MaaS is the Open Data driver and enables Open Data portability into the Cloud.

Data models used as a service mainly provide the following topics:

  • Implementing and sharing data structure models;
  • Verifying data model properties according to private and public cloud requirements;
  • Designing and testing new query types. Specific query classes need to support heterogeneous data;
  • Designing of the data storage model. The model should enable query processing directly against databases to ensure privacy and secure changes from data updates and review;
  • Modeling data to predict usage “early”;
  • Portability, a central property when data is shared among fields of application;
  • Sharing, redistribution and participation of data among datasets and applications.

As a consequence, the data should be available as a whole and at a reasonable fee, preferably by finding, navigating and downloading over the Cloud. It should also be available in a usable and changeable form. This means modeling Open Data and then using the models to map location and usage, configuration, integration and changes along the Open Data lifecycle.

What is MaaS
Data models can be shared, off-line tested and verified to define data designing requirements, data topology, performance, placement and deployment. This means models themselves can be supplied as a service to allow providers to verify how and where data has to be designed to meet the Cloud service’s requisites: this is MaaS. As a consequence by using MaaS, Open Data designers can verify “on-premise” how and why datasets meet Open Data requirements. With this approach, Open Data models can be tuned on real usage and then mapped “on-premise” to the public body’s service. Further, MaaS inherits all the defined service’s properties and so the data model can be reused, shared and classified for new Open Data design and publication.

Open Data implementation is MaaS (Model as a Service) driven
Open Data is completely supported by data modeling and then MaaS completely supports Open Data. MaaS should be the first practice, helping to tune analysis and Open Data design. Furthermore, data models govern design, deployment, storage, changes, resources allocation, hence MaaS supports:

  • Applying Best Practice for Open Data design;
  • Classifying Open Data field of application;
  • Designing Open Data taxonomy and integration;
  • Guiding Open Data implementation;
  • Documenting data maturity and evolution by applying DaaS lifecycle.

Accordingly, Maas provides “on-premise” properties supporting Open Data design and publication:

  1. AnalysisWhat data are you planning to make open? When working with MaaS, a data model is used to perform data analysis. This means the Open Data designer might return to this step to correct, update and improve the incoming analysis: he always works on an “on-premise” data model. Analysis performed by model helps in identifying data integration and interoperability. The latter assists in choosing what data has to be published and in defining open datasets;
  2. DesignDuring the analysis step, the design is carried out too. The design can be changed and traced along the Open Data lifecycle. Remember that with MaaS the model is a service, and the data opened offers the designed service;
  3. Data securityData security becomes the key property to rule data access and navigation. MaaS plays a crucial role in data security: in fact, the models contain all the infrastructure properties and include information to classify accesses, classes of users, perimeters and risk mitigation assets. Models are the central way to enable data protection within the Open Data device;
  4. Participation - Because the goal is “everyone must be able to use Open Data”, participation is comprehensive of people and groups without any discrimination or restriction. Models contain data access rules and accreditations (open licensing).
  5. Mapping – The MaaS mapping property is important because many people can obtain the data after long navigation and several “bridges” connecting different fields of applications. Looking at this aspect, MaaS helps the Open Data designer to define the best initial “route” between transformation and aggregation linking different areas. Then continually engaging citizens, developers, sector’s expert, managers … helps in modifying the model to better update and scale Open Data contents: the easier it is for outsiders to discover data, the faster new and useful Open Data services will be built.
  6. OntologyDefining metadata vocabulary for describing ontologies. Starting from standard naming definition, data models provide grouping and reorganizing vocabulary for further metadata re-use, integration, maintenance, mapping and versioning;
  7. Portability – Models contain all the properties belonging to data in order that MaaS can enable Open Data service’s portability to the Cloud. The model is portable by definition and it can be generated to different database and infrastructures;
  8. Availability – The DaaS lifecycle assures structure validation in terms of MaaS accessibility;
  9. Reuse and distribution – Open Data can include merging with additional datasets belonging to other fields of application (for example, medical research vs. air pollution). Open Data built by MaaS has this advantage. Merging open datasets means merging models by comparing and synchronizing, old and new versions, if needed;
  10. Change Management and History – Data models are organized in libraries to preserve Open Data changes and history. Changes are traced and maintained to restore, if necessary, model and/or datasets;
  11. Redesign – Redesigning Open Data, means redesigning the model it belongs to: the  model drives the history of the changes;
  12. Fast BI – Publishing Open Data is an action strictly related to the BI process. Redesigning and publishing Open Data are two automated steps starting from the design of the data model and from its successive updates.

MaaS is the emerging solution for Open Data implementation. Open Data is public and private accessible data, designed to connect the social community with the public bodies. This data should be made available without restriction although it is placed under security and open licensing. In addition, Open Data is always up-to-date and transformation and aggregation have to be simple and time saving for inesperienced users. To achieve these goals, the Open Data service has to be model driven designed and providing data integration, interoperability, mapping, portability, availability, security, distribution, all properties assured by applying MaaS.

[1] N. Piscopo - ERwin® in the Cloud: How Data Modeling Supports Database as a Service (DaaS) Implementations
[2] N. Piscopo - CA ERwin® Data Modeler’s Role in the Relational Cloud
[3] N. Piscopo - DaaS Contract templates: main constraints and examples, in press
[4] D. Burbank, S. Hoberman - Data Modeling Made Simple with CA ERwin® Data Modeler r8
[7] N. Piscopo – Best Practices for Moving to the Cloud using Data Models in theDaaS Life Cycle
[8] N. Piscopo – Using CA ERwin® Data Modeler and Microsoft SQL Azure to Move Data to the Cloud within the DaaS Life Cycle
[9] The Open Software Service Definition (OSSD) at

Read the original blog entry...

More Stories By Cloud Best Practices Network

The Cloud Best Practices Network is an expert community of leading Cloud pioneers. Follow our best practice blogs at

@CloudExpo Stories
Too often with compelling new technologies market participants become overly enamored with that attractiveness of the technology and neglect underlying business drivers. This tendency, what some call the “newest shiny object syndrome” is understandable given that virtually all of us are heavily engaged in technology. But it is also mistaken. Without concrete business cases driving its deployment, IoT, like many other technologies before it, will fade into obscurity.
Discussions of cloud computing have evolved in recent years from a focus on specific types of cloud, to a world of hybrid cloud, and to a world dominated by the APIs that make today's multi-cloud environments and hybrid clouds possible. In this Power Panel at 17th Cloud Expo, moderated by Conference Chair Roger Strukhoff, panelists addressed the importance of customers being able to use the specific technologies they need, through environments and ecosystems that expose their APIs to make true ...
Microservices are a very exciting architectural approach that many organizations are looking to as a way to accelerate innovation. Microservices promise to allow teams to move away from monolithic "ball of mud" systems, but the reality is that, in the vast majority of organizations, different projects and technologies will continue to be developed at different speeds. How to handle the dependencies between these disparate systems with different iteration cycles? Consider the "canoncial problem"...
The Internet of Things is clearly many things: data collection and analytics, wearables, Smart Grids and Smart Cities, the Industrial Internet, and more. Cool platforms like Arduino, Raspberry Pi, Intel's Galileo and Edison, and a diverse world of sensors are making the IoT a great toy box for developers in all these areas. In this Power Panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists discussed what things are the most important, which will have the most profound...
Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. Get ready to learn the facts: Is there a bias against women in the tech / developer communities? Why are women 50% of the workforce, but hold only 24% of the STEM or IT positions? Some beginnings of what to do about it! In her Day 2 Keynote at 17th Cloud Expo, San...
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Ben Perlmutter, a Sales Engineer with IBM Cloudant, demonstrated techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, faster user e...
In today's enterprise, digital transformation represents organizational change even more so than technology change, as customer preferences and behavior drive end-to-end transformation across lines of business as well as IT. To capitalize on the ubiquitous disruption driving this transformation, companies must be able to innovate at an increasingly rapid pace. Traditional approaches for driving innovation are now woefully inadequate for keeping up with the breadth of disruption and change facin...
I recently attended and was a speaker at the 4th International Internet of @ThingsExpo at the Santa Clara Convention Center. I also had the opportunity to attend this event last year and I wrote a blog from that show talking about how the “Enterprise Impact of IoT” was a key theme of last year’s show. I was curious to see if the same theme would still resonate 365 days later and what, if any, changes I would see in the content presented.
Cloud computing delivers on-demand resources that provide businesses with flexibility and cost-savings. The challenge in moving workloads to the cloud has been the cost and complexity of ensuring the initial and ongoing security and regulatory (PCI, HIPAA, FFIEC) compliance across private and public clouds. Manual security compliance is slow, prone to human error, and represents over 50% of the cost of managing cloud applications. Determining how to automate cloud security compliance is critical...
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data...
Just over a week ago I received a long and loud sustained applause for a presentation I delivered at this year’s Cloud Expo in Santa Clara. I was extremely pleased with the turnout and had some very good conversations with many of the attendees. Over the next few days I had many more meaningful conversations and was not only happy with the results but also learned a few new things. Here is everything I learned in those three days distilled into three short points.
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo 2016 in New York and Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place Nov 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 17th Cloud Expo and will feature technical sessions from a rock star conference faculty ...
In his General Session at DevOps Summit, Asaf Yigal, Co-Founder & VP of Product at, explored the value of Kibana 4 for log analysis and provided a hands-on tutorial on how to set up Kibana 4 and get the most out of Apache log files. He examined three use cases: IT operations, business intelligence, and security and compliance. Asaf Yigal is co-founder and VP of Product at log analytics software company In the past, he was co-founder of social-trading platform Currensee, which...
DevOps is about increasing efficiency, but nothing is more inefficient than building the same application twice. However, this is a routine occurrence with enterprise applications that need both a rich desktop web interface and strong mobile support. With recent technological advances from Isomorphic Software and others, rich desktop and tuned mobile experiences can now be created with a single codebase – without compromising functionality, performance or usability. In his session at DevOps Su...
As organizations realize the scope of the Internet of Things, gaining key insights from Big Data, through the use of advanced analytics, becomes crucial. However, IoT also creates the need for petabyte scale storage of data from millions of devices. A new type of Storage is required which seamlessly integrates robust data analytics with massive scale. These storage systems will act as “smart systems” provide in-place analytics that speed discovery and enable businesses to quickly derive meaningf...
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu’s platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
In his General Session at 17th Cloud Expo, Bruce Swann, Senior Product Marketing Manager for Adobe Campaign, explored the key ingredients of cross-channel marketing in a digital world. Learn how the Adobe Marketing Cloud can help marketers embrace opportunities for personalized, relevant and real-time customer engagement across offline (direct mail, point of sale, call center) and digital (email, website, SMS, mobile apps, social networks, connected objects).
The buzz continues for cloud, data analytics and the Internet of Things (IoT) and their collective impact across all industries. But a new conversation is emerging - how do companies use industry disruption and technology enablers to lead in markets undergoing change, uncertainty and ambiguity? Organizations of all sizes need to evolve and transform, often under massive pressure, as industry lines blur and merge and traditional business models are assaulted and turned upside down. In this new da...
Culture is the most important ingredient of DevOps. The challenge for most organizations is defining and communicating a vision of beneficial DevOps culture for their organizations, and then facilitating the changes needed to achieve that. Often this comes down to an ability to provide true leadership. As a CIO, are your direct reports IT managers or are they IT leaders? The hard truth is that many IT managers have risen through the ranks based on their technical skills, not their leadership ab...
We all know that data growth is exploding and storage budgets are shrinking. Instead of showing you charts on about how much data there is, in his General Session at 17th Cloud Expo, Scott Cleland, Senior Director of Product Marketing at HGST, showed how to capture all of your data in one place. After you have your data under control, you can then analyze it in one place, saving time and resources.